Gartner Research

Hype Cycle for Data Science, 2016

Published: 25 July 2016

ID: G00303293

Analyst(s): Jim Hare , Alexander Linden , Peter Krensky


Advances in data science are sparking more creative business opportunities. While much of the hype is for artificial intelligence and deep learning, this Hype Cycle shows the breadth and depth of excitement about data science, with new technologies and some significant movements from last year.

Table Of Contents


  • What You Need to Know
  • The Hype Cycle
  • The Priority Matrix
  • Off the Hype Cycle
  • On the Rise
    • Probability Management
    • Guided Analytics
    • Algorithm Marketplaces
    • Deep Reinforcement Learning
    • Edge Analytics
    • Model Factory
    • Notebooks
    • Advanced Anomaly Detection
    • Citizen Data Science
    • Smart Data Discovery
    • Cognitive Computing
    • Graph Analytics
  • At the Peak
    • Optimization
    • Prescriptive Analytics
    • Python
    • Deep Neural Nets
    • Event Stream Processing
    • Machine Learning
    • Self-Service Data Preparation
    • Data Lakes
    • Spark
    • Predictive Analytics
    • Hadoop-Based Data Discovery
  • Sliding Into the Trough
    • Natural-Language Question Answering
    • Model Management
    • Speech Analytics
  • Climbing the Slope
    • Text Analytics
    • Video/Image Analytics
    • Ensemble Learning
    • Simulation
  • Entering the Plateau
    • R
  • Appendixes
    • Hype Cycle Phases, Benefit Ratings and Maturity Levels

Gartner Recommended Reading

©2021 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates. This publication may not be reproduced or distributed in any form without Gartner’s prior written permission. It consists of the opinions of Gartner’s research organization, which should not be construed as statements of fact. While the information contained in this publication has been obtained from sources believed to be reliable, Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartner research may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such. Your access and use of this publication are governed by Gartner’s Usage Policy. Gartner prides itself on its reputation for independence and objectivity. Its research is produced independently by its research organization without input or influence from any third party. For further information, see Guiding Principles on Independence and Objectivity.

Already have a Gartner Account?

Become a client

Learn how to access this content as a Gartner client.